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ISDS Annual Conference Proceedings 2012. This is an Open Access article distributed under the terms of the Creative Commons Attribution-
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ISDS 2012 Conference Abstracts

Development of Automated Data Quality Indicators and
Visualizations using Florida’s ESSENCE System
Wayne Loschen*1 and Aaron Kite-Powell2

1Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA; 2Florida Department of Health, Jacksonville, FL, USA

Objective
The objective of this project was to develop visualizations and

tools for public health users to determine the quality of their surveil-
lance data. Users should be able to determine or be warned when sig-
nificant changes have occurred to their data streams, such as a
hospital converting from a free-text chief complaint to a pick list.
Other data quality factors, such as individual variable completeness
and consistency in how values are mapped to standard system selec-
tions should be available to users. Once built, these new visualiza-
tions should also be evaluated to determine their usefulness in a
production disease surveillance system.

Introduction
Understanding your data is a fundamental pillar of disease sur-

veillance success. With the increase in automated, electronic surveil-
lance tools many public health users have begun to rely on those tools
to produce reports that contain processed results to perform their daily
jobs. These tools can focus on the algorithm or visualizations needed
to produce the report, and can easily overlook the quality of the in-
coming data. The phrase “garbage in, garbage out” is often used to de-
scribe the value of reports when the incoming data is not of high
quality. There is a need then, for systems and tools that help users de-
termine the quality of incoming data.

Methods
A series of data quality visualizations were developed and imple-

mented in the Florida Department of Health’s version of ESSENCE.
Users were given numerous pages that showed different aspects of
data quality, such as variable-level percent completeness measure-
ments shown by hospital or county. Other items included the percent
of time a value that should have been a part of a specific reference list
was actually present and matched to known values, the number of
input files received by a hospital, and the time each data source was
processed. Finally, an algorithm and visualization was developed to
alert users when data quality factors had changed significantly. With

access to all these new screens, users of the system were given the op-
portunity to use the system and their usage and opinions were col-
lected.

Results
The data quality portal has been active the Florida ESSENCE sys-

tem since March 31st, 2012. Between that time and August the por-
tal has been accessed over 1300 times. The presentation will include
additional statistics about which specific features were most used and
those features that users have found the most useful. In addition, data
quality issues that have been discovered using the new tool will be
discussed.

Conclusions
With the ever increasing amount of data that public health must

analyze due to meaningful use, it is imperative that tools and visual-
izations that can decipher data quality issues be made available in an
easily accessible format and without the need for tools external to the
system. If systems continue to ignore changes in the data they receive
automatically, it can easily produce degraded or incorrect analyses
and interpretation of events, leading to wasted resources. These re-
sults can negatively impact the decisions and responses that public
health users make, especially in light of the increasing reliance on
these types of systems for up to the minute information. This project
has developed tools and visualizations that can help determine the
data quality issues as they are occurring. This presentation will out-
line the lessons learned for using and creating these tools so they can
be shared for everyone to benefit.

Keywords
Visualization; Data Quality; Meaningful Use

*Wayne Loschen
E-mail: wayne.loschen@jhuapl.edu

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e17, 2013